Datasets:
Tasks:
Text Classification
Languages:
Chinese
Multilinguality:
monolingual
Size Categories:
100K<n<20M
Language Creators:
shibing624
Annotations Creators:
shibing624
Source Datasets:
https://github.com/shibing624/text2vec
https://github.com/IceFlameWorm/NLP_Datasets/tree/master/ATEC
http://icrc.hitsz.edu.cn/info/1037/1162.htm
ArXiv:
Tags:
License:
# -*- coding: utf-8 -*- | |
""" | |
@author:XuMing(xuming624@qq.com) | |
@description: | |
""" | |
"""Natural Language Inference (NLI) Chinese Corpus.(nli_zh)""" | |
import os | |
import datasets | |
_DESCRIPTION = """纯文本数据,格式:(sentence1, sentence2, label)。常见中文语义匹配数据集,包含ATEC、BQ、LCQMC、PAWSX、STS-B共5个任务。""" | |
ATEC_HOME = "https://github.com/IceFlameWorm/NLP_Datasets/tree/master/ATEC" | |
BQ_HOME = "http://icrc.hitsz.edu.cn/info/1037/1162.htm" | |
LCQMC_HOME = "http://icrc.hitsz.edu.cn/Article/show/171.html" | |
PAWSX_HOME = "https://arxiv.org/abs/1908.11828" | |
STSB_HOME = "https://github.com/pluto-junzeng/CNSD" | |
_CITATION = "https://github.com/shibing624/text2vec" | |
_DATA_URL = "https://github.com/shibing624/text2vec/releases/download/1.1.2/senteval_cn.zip" | |
class NliZhConfig(datasets.BuilderConfig): | |
"""BuilderConfig for NLI_zh""" | |
def __init__(self, features, data_url, citation, url, label_classes=(0, 1), **kwargs): | |
"""BuilderConfig for NLI_zh | |
Args: | |
features: `list[string]`, list of the features that will appear in the | |
feature dict. Should not include "label". | |
data_url: `string`, url to download the zip file from. | |
citation: `string`, citation for the data set. | |
url: `string`, url for information about the data set. | |
label_classes: `list[int]`, sim is 1, else 0. | |
**kwargs: keyword arguments forwarded to super. | |
""" | |
super().__init__(version=datasets.Version("1.0.0"), **kwargs) | |
self.features = features | |
self.label_classes = label_classes | |
self.data_url = data_url | |
self.citation = citation | |
self.url = url | |
class NliZh(datasets.GeneratorBasedBuilder): | |
"""The Natural Language Inference Chinese(NLI_zh) Corpus.""" | |
BUILDER_CONFIGS = [ | |
NliZhConfig( | |
name="ATEC", | |
description=_DESCRIPTION, | |
features=["sentence1", "sentence1"], | |
data_url=_DATA_URL, | |
citation=_CITATION, | |
url=ATEC_HOME, | |
), | |
NliZhConfig( | |
name="BQ", | |
description=_DESCRIPTION, | |
features=["sentence1", "sentence1"], | |
data_url=_DATA_URL, | |
citation=_CITATION, | |
url=BQ_HOME, | |
), | |
NliZhConfig( | |
name="LCQMC", | |
description=_DESCRIPTION, | |
features=["sentence1", "sentence1"], | |
data_url=_DATA_URL, | |
citation=_CITATION, | |
url=LCQMC_HOME, | |
), | |
NliZhConfig( | |
name="PAWSX", | |
description=_DESCRIPTION, | |
features=["sentence1", "sentence1"], | |
data_url=_DATA_URL, | |
citation=_CITATION, | |
url=PAWSX_HOME, | |
), | |
NliZhConfig( | |
name="STS-B", | |
description=_DESCRIPTION, | |
features=["sentence1", "sentence1"], | |
data_url=_DATA_URL, | |
citation=_CITATION, | |
url=STSB_HOME, | |
), | |
] | |
def _info(self): | |
return datasets.DatasetInfo( | |
description=self.config.description, | |
features=datasets.Features( | |
{ | |
"sentence1": datasets.Value("string"), | |
"sentence2": datasets.Value("string"), | |
"label": datasets.Value("int32"), | |
# "idx": datasets.Value("int32"), | |
} | |
), | |
homepage=self.config.url, | |
citation=self.config.citation, | |
) | |
def _split_generators(self, dl_manager): | |
dl_dir = dl_manager.download_and_extract(self.config.data_url) or "" | |
dl_dir = os.path.join(dl_dir, f"senteval_cn/{self.config.name}") | |
return [ | |
datasets.SplitGenerator( | |
name=datasets.Split.TRAIN, | |
gen_kwargs={ | |
"filepath": os.path.join(dl_dir, f"{self.config.name}.train.data"), | |
}, | |
), | |
datasets.SplitGenerator( | |
name=datasets.Split.VALIDATION, | |
gen_kwargs={ | |
"filepath": os.path.join(dl_dir, f"{self.config.name}.valid.data"), | |
}, | |
), | |
datasets.SplitGenerator( | |
name=datasets.Split.TEST, | |
gen_kwargs={ | |
"filepath": os.path.join(dl_dir, f"{self.config.name}.test.data"), | |
}, | |
), | |
] | |
def _generate_examples(self, filepath): | |
"""This function returns the examples in the raw (text) form.""" | |
with open(filepath, 'r', encoding="utf-8") as f: | |
for idx, row in enumerate(f): | |
# print(row) | |
terms = row.split('\t') | |
yield idx, { | |
"sentence1": terms[0], | |
"sentence2": terms[1], | |
"label": int(terms[2]), | |
} | |